In manufacturing of pulp and paper, the production is typically divided in a number of process sections connected to each other in a more or less complex pattern. Examples of process sections could be digesters, washing arrangements, refiners, bleaching arrangements, etc. The part process of each process section is typically a complex process, where the output flow from the process section and its properties depends on the present input flow (including its properties) of material, chemical additives, process operational conditions as well as of the previous history of operation of the process section. This means that the output is not only dependent on present conditions, but also on how the process section was operated in an earlier stage, i.e. there is a dynamic relation between variables of different kinds.
In pulp and paper production, a lot of chemical substances are added during the process. These process chemicals normally react and form other chemical substances when performing their intended action upon the pulp and/or paper. However, some chemical substances are to a large extent extracted from the process, to keep the concentrations within required limits. Since the chemical substances are expensive, as much as possible is collected and recovered. A pulp and paper production line therefore typically comprises also process sections taking care of extracted chemical substances. The flow and properties of such chemical substances through the process are connected to operational conditions in an even more complex manner. In particular, the dependence on process history is even more pronounced than for the pulp flow itself. In most pulp and paper mills of today, control of the flow of chemical additives is typically of a very simple type. If a shortage of chemicals appears, more chemicals are added, if an excess of chemicals appears, the excess is wasted.
In the European Patent Application EP 1 035 253, an on-line optimized pulp or paper production process is disclosed. In this disclosure, a number of inputs, such as raw material as well as chemicals, energy etc. are mentioned as important to optimize the process. The outputs, which are considered, are typically production quantity, quality properties, and price as well as waste product quantities. However, the actual optimizing procedure is only described in general terms as an automatically calibrating module. The method is probably intended for off-line optimization of set-points in different typical steady-state situations. Difficulties arising from differences in the previous history of operation are not addressed at all. Furthermore, the optimization basically concerns the process as one entity, where only inputs and outputs of the entire process are discussed, even if bottleneck problems are mentioned.
Problems arising from dependence of operation history becomes particularly accentuated when the operation of the process is changed, e.g. if the production rate is changed. Also large variations in the properties of the raw material, e.g. large kappa number changes or a change between hardwood and softwood, may cause large changes to the process. In such cases, large and slow fluctuations may be induced in the process system. Some fluctuations may even have time constants exceeding several hours. Models and optimization procedures, which are focused in the present outcome of the process, may therefore introduce control measures, which much later may turn out to be unfavourable. In cases where the changes in process operation are large and/or abrupt, it may not even be possible to maintain required quality, and operate the mill close to the most profitable state. Fluctuations are generally connected with actions, which eventually end up with increased waste of e.g. chemical additives, which in turn is connected to large costs. These fluctuations are difficult to handle in prior art control systems.
Control systems according to prior art are typically based on an assumption of a substantially failure-free operation. In case a failure occurs and a process section temporarily has to be taken out of operation, there might not be enough buffers ensuring a continuous operation for the rest of the process sections. Such discontinuities may affect both the quality and the quantity of the end product as well as other cost related properties. In particular in systems having pronounced bottlenecks, problems with continuity may occur during minor disruptions.